Halftoning is a printing process that is used to represent a continuous grey-scale or colour signal by an array of dots of selected size/s that are placed in selected positions. The size and spacing of the dots is such that the printed document appears almost identical to the original continuous signal to the naked eye. The concept of halftone removal is relatively new due to a recent increase in the number of computer-based applications for processing scanned images for example in order to generate a compact electronic representation of the original documents.
One of the most common forms of halftoning is known as clustered-dot halftoning. In this method of halftoning, dots of varying sizes are placed on a regular grid during printing to visually represent the original continuous signal. Clustered-dot halftoning is used in modern printing techniques such as offset printing for producing magazines, brochures, etc., and in black and white laser printers.
In grey-scale clustered-dot halftoning, dots are placed on a regular grid according to a fixed spacing and a fixed angle. The inverse of the average dot spacing is known as the screen frequency and the average angle is known as the screen angle. An example of grey-scale clustered-dot halftoning applied to the image shown in FIG. 1a is shown in FIG. 1b, where the screen frequency and screen angle are depicted as Fs and θ, respectively. In colour printing, such as with CMYK (cyan, magenta, yellow, black), each colour channel is placed on a fixed screen frequency grid, but with a different screen angle for each channel. An example of such halftoning applied to the image shown in FIG. 1c is shown in FIG. 1d, where the screen angles for the cyan, magenta, yellow and black colour channels are depicted as θc, θm, θy and θk, respectively. The different angles for each channel minimise interference patterns that may result from placement of the dot patterns relating to each channel on top of one another.
Modern inkjet printers use a technique known as dispersed-dot halftoning, which disperses dots within a local area in a non-regular fashion. Dispersed-dot halftoning is particularly suited to printing methods that are capable of controlling dot placement, shape and size to a high degree of accuracy.
A number of existing methods for removing halftone are briefly described hereinafter.
Low-pass filtering or blurring is the simplest method for removing halftone and can be effective if an image to be processed contains little high frequency information (e.g., a soft-focus photograph). However, if the image contains significant high frequency information such as sharp edges of text characters or graphic objects, these will be lost during low-pass filtering or blurring. This disadvantageously renders the method unsuitable for general use.
Look-up table methods use a set of training images that correspond to different types of fixed halftone patterns. Statistics relating to the mapping between each type of halftone and a corresponding correct continuous tone representation are collected. For an actual runtime image portion, the closest match in the look-up table is used to obtain the best parameters to map the halftone to continuous tone. A disadvantage with look-up table methods is that representative training data is required for each halftone type that is likely to be encountered in normal usage. Disadvantageously, training for combination regions containing both halftone and non-halftone, such as text superimposed on a photograph, is difficult.
Wavelet based methods exploit spatial-frequency information to low-pass filter images in regions where there are no edges, and low-pass filter images with a higher cut-off frequency in regions where edges do exist. In order for such methods to be successful, however, a reasonably large portion of an image (e.g., 512×512 pixels) must be processed at any one time. This disadvantageously increases the computational complexity required.
Projection methods are iterative procedures that attempt to estimate the original halftone kernel by starting with an initial estimate and subsequently converging within certain constraints. Sufficient convergence is associated with an output image that is a sensible continuous tone representation of the original image. As projection methods use an iterative procedure, such methods are generally unsuitable for applications that require a fast, fixed-time method for processing an image and removing halftone.
Binary-only methods are designed for bi-level images. Such methods examine the local statistics of binary halftoning to determine how to best represent the halftoning as a continuous tone. Binary-only methods are thus not suitable for continuous tone scanned images.
Frequency masking of colour halftones has been used for images containing only halftone, such as photographs. Such methods first convolve a box filter over the entire image and subsequently transform regions of the image (e.g., 256×256 pixel regions) into the frequency domain by means of a Fast Fourier Transform (FFT). The dominant peaks in each region are located and a Fourier filter is constructed to attenuate the peak frequencies in each region. An inverse FFT is then applied to each region to return to the spatial domain. Disadvantageously, such methods have been designed for regions containing only halftone. Furthermore, such methods rely on time consuming algorithms to accurately determine the locations of peaks in the frequency domain and process a relatively large portion of the image at any one time.
A need thus exists to provide methods, apparatuses and computer program products for detecting and removing halftone in images that overcome or at least ameliorate one or more disadvantages associated with existing arrangements.